کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5741923 1617196 2017 5 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Combining expert knowledge with machine learning on the basis of fuzzy training
ترجمه فارسی عنوان
ترکیب دانش تخصصی با یادگیری ماشین بر اساس آموزش فازی
کلمات کلیدی
مدلسازی فازی دانش کارشناس، فراگیری ماشین، تنظیم غیرخطی، بهینه سازی، مدل سازی عملکرد
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک بوم شناسی، تکامل، رفتار و سامانه شناسی
چکیده انگلیسی


- We introduced a fuzzy training approach based on nonlinear regularization.
- The aim is to find a compromise between expert knowledge and training.
- An open source implementation in Python/Cython is available.
- The fuzzy training was verified using more than 4500 sugar beet yield record.

The paper introduces a fuzzy training approach based on nonlinear regularization in an effort to avoid over training. The main idea is to restrict training so that the basic expert knowledge used to build the model is still visible. This is implemented by a new nonlinear regularization approach which can be applied to any kind of training data set. The approach is demonstrated using a large crop yield data set (>4500 field records) for sugar beet collected in agricultural farms over a 14-year period (1976-1989) in East Germany. The software is implemented in SAMT2, free and open source software, using the Python programming language.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Informatics - Volume 38, March 2017, Pages 26-30
نویسندگان
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